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Related lectures (31)

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Statistical Inference: Linear Models

Explores statistical inference for linear models, covering model fitting, parameter estimation, and variance decomposition.

Modeling Response Surfaces in Matlab

Covers modeling response surfaces in Matlab, including building the model, defining the domain, computing values, and analyzing residuals.

Design of Experiments: Response Surface

Explores experimental design methodology, including classic plans, simplex method, and canonical analysis for linear and quadratic models.

Linear Regression: Simple

Introduces simple linear regression, properties of residuals, variance decomposition, and the coefficient of determination in the context of Okun's law.

Analysis of Variance (ANOVA)

Covers Analysis of Variance (ANOVA) for assessing categorical variable effects on quantitative outcomes.

Model Selection

Covers model selection, emphasizing the tradeoff between complexity and error in data analysis.

Regression II

Delves into regression analysis, emphasizing distributional checks, weighted least squares, and hypothesis testing.

Regression: Simple and Multiple Linear

Covers simple and multiple linear regression, including least squares estimation and model diagnostics.

Pizza Making Process

Covers the process of making pizza, sampling, averages, dispersion, residuals, and normal distribution.

Probability and Estimation in Statistics

Introduces probability, estimation methods, linear models, testing, and advanced regression techniques.